204 citations · 630 across the 36 of their papers we have counts for
39 papers
Multi-Rater Calibrated Segmentation Models
Meritxell Riera-Marín, Javier García López, Júlia Rodríguez-Comas +2
Objective: Accurate probability estimates are essential for the safe deployment of medical image segmentation models in clinical decision-making. However, modern deep segmentation…
Assessing Pancreatic Ductal Adenocarcinoma Vascular Invasion: the PDACVI Benchmark
M. Riera-Marín, O. K. Sikha, J. Rodríguez-Comas +23
Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion…
AI for Mycetoma Diagnosis in Histopathological Images: The MICCAI 2024 Challenge
Hyam Omar Ali, Sahar Alhesseen, Lamis Elkhair +19
Mycetoma is a neglected tropical disease caused by fungi or bacteria leading to severe tissue damage and disabilities. It affects poor and rural communities and presents medical ch…
Is Synthetic Image Augmentation Useful for Imbalanced Classification Problems? Case-Study on the MIDOG2025 Atypical Cell Detection Competition
Leire Benito-Del-Valle, Pedro A. Moreno-Sánchez, Itziar Egusquiza +4
The MIDOG 2025 challenge extends prior work on mitotic figure detection by introducing a new Track 2 on atypical mitosis classification. This task aims to distinguish normal from a…
Uncertainty-Aware Segmentation Quality Prediction via Deep Learning Bayesian Modeling: Comprehensive Evaluation and Interpretation on Skin Cancer and Liver Segmentation
Sikha O K, Meritxell Riera-Marín, Adrian Galdran +4
Image segmentation is a critical step in computational biomedical image analysis, typically evaluated using metrics like the Dice coefficient during training and validation. Howeve…
Calibration and Uncertainty for multiRater Volume Assessment in multiorgan Segmentation (CURVAS) challenge results
Meritxell Riera-Marin, Sikha O K, Julia Rodriguez-Comas +29
Deep learning (DL) has become the dominant approach for medical image segmentation, yet ensuring the reliability and clinical applicability of these models requires addressing key…